Importers are responsible for two tasks: (1) Convert a given DNN model into SoftNeuro's
format, and (2) Optimize the computational graph of the model. Importers currently support conversion from
TensorFlow [1]} and ONNXhttps://onnx.ai/ (which in turn
supports Caffe2 [2]}, Chainer [3]}, Microsoft Cognitive
Toolkit [4]}, MXNet [5]}, PyTorch [6]}, and
PaddlePaddle [7]}). When converting a model, importers automatically
optimize the model's computational graph. For instance, ReLU activation and batch
normalization layers are fused into their previous layers, reducing computational
cost without affecting accuracy.
